Comparison between different frameworks in Visual Object Tracking
Konferenz: CIBDA 2022 - 3rd International Conference on Computer Information and Big Data Applications
25.03.2022 - 27.03.2022 in Wuhan, China
Tagungsband: CIBDA 2022
Seiten: 6Sprache: EnglischTyp: PDF
Autoren:
Lu, Yifan (International College Chongqing University of Posts and Telecommunications Chongqing, China)
Luo, Yayun (School of Automobile and Mechanical Engineering Changsha University of Science & Technology Changsha, China)
Inhalt:
In recent years, deep learning-based visual tracking has flourished and a number of advances have been made. Numerous frameworks have been proposed to improve the accuracy and robustness. In this paper, we focus on introducing several different modified methods of visual tracking. We summarize the tracking framework as Siamese network, and correlation filter based methods. We review 10 distinguish methods published recently. We state that our review aims to provide an in-depth introduction on visual object tracking, which can guide the beginners to fast recognize this task.